Jobs at M-Files

The AI Native Engineer role focuses on building AI-native software delivery capabilities, utilizing modern software engineering practices, quality automation, and cloud platforms, particularly within the Microsoft ecosystem.

Consult with customers and partners to define business requirements and design M-Files-based solutions. Plan scalable, maintainable implementations, integrate M-Files with other IT systems, document specifications, resolve technical issues, and contribute to continuous improvement of implementation practices.

Partner with customers to analyze industry-specific business needs and implement M-Files document and knowledge management solutions. Lead small-to-mid implementations, define requirements, integrate with existing systems, provide training, support pre-sales, advise on automation and compliance, and ensure customer satisfaction across targeted verticals.

Lead product marketing for M-Files AI platform and cloud: define platform positioning and FedRAMP messaging, drive GTM launches and content, deliver competitive intelligence, enable sales and partners, and represent the company in events and analyst briefings to increase adoption and pipeline.

Lead and execute engineering operations transformation across product and engineering teams. Drive AI adoption, improve processes, embed measurable outcomes, build dashboards, coach leaders, ensure quality launches, and manage cross-functional change projects end-to-end.

As a Systems Specialist, you will configure M-Files for customers, consult on projects, and support business process development, requiring teamwork and communication skills.

As a Senior Solution Architect, you will design and implement M-Files solutions, consult on business processes, and manage customer projects.

Configure M-Files to meet customer needs, support customers with business process development, and manage impactful implementations.

Design, deploy, and run an AI-first product development lifecycle for PM teams: own tooling, discovery pipelines, AI augmentation standards, PM capability building, instrumentation of PM metrics, and operationalize outcomes tied to ARR and product adoption.